
Fugu Ultra vs Gemma-4 12B Coder
Sakana's multi-agent answer to Fusion — frontier ensemble without single-vendor risk. vs The free, offline coder — trained only on code that passed its tests.
Head-to-head verdict: Fugu Ultra wins 2–0.
What I tested — same prompt, two models
I run the same fixed prompt set through every new model the day it drops — same string, one shot, single HTML file out — and I score the result 0–10 on whether it ran, how close it hit the brief, and how good it looked. Below is what came out when I gave the exact same prompts to Fugu Ultra and Gemma-4 12B Coder, side by side, on 2 shared tasks inside the Agent Operating System.
Both models were given identical prompts inside the Agent Operating System — no help, no iteration, no "best of N" tricks. I run each prompt once, save the HTML file the model produces, and score it 0–10 on whether it ran, how close it hit the brief, and how good it looked. The scoring is mine. The verdicts below are pulled from my source comparison guides at agentos.guide where I publish every score and the reasoning behind it.
Fugu Ultra · Dispatched from Agent OS as the panel-ensemble alternative to OpenRouter Fusion. Bench scored by Claude judge against the same 42 prompts as every other model.
Gemma-4 12B Coder · Wired into the Agent OS local engine (Local chat + Local Hermes Engine + Agent Kanban) as the free, offline coder. Scored by Claude judge against the same one-shot prompts every other model ran.
Side-by-side on 9 shared tasks
Click any cell to play that model's actual one-shot attempt. Medals are derived from my 0–10 scores per task (highest = 🥇, second = 🥈, third = 🥉).
Where Fugu Ultra beat Gemma-4 12B Coder
The tasks where I gave Fugu Ultra a higher 0–10 score on the same prompt — with the actual commentary from my source guides.
What I saw: 26KB three.js spiral galaxy with drag-to-orbit + dust lanes + bloom. Comparable visual quality to Fusion's 14KB attempt with more polish on the camera UI. ~$0.24 per call.
What I saw: Sakana Fugu Ultra shipped a 32KB Apple-keynote landing — bigger than Fusion's 20KB attempt at the same prompt. Animated mesh gradient, multi-section, polished. $0.32 vs Fusion's $1.30 for the same output — 4× cheaper, denser result.
Strengths & weaknesses I logged
Fugu Ultra
Strengths
- SWE Bench Pro 73.7 · GPQA-D 95.5 · MRCRv2 93.6 — Sakana's published frontier-tier benchmark scores
- Vendor-agnostic ensemble — opt out of specific providers for compliance / export-control
- OpenAI-compatible API at api.sakana.ai — drop-in for existing tooling
Trade-offs
- Panel orchestration adds latency — even a 'pong' burns ~2k orchestration tokens
- Newer than Fusion; less community calibration on long-tail prompts
Gemma-4 12B Coder
Strengths
- Runs 100% free + offline on a consumer Mac (Q4_K_M, 7.4GB) — no API, no rate limits, nothing leaves the machine
- Test-verified training (Composer 2.5 + Fable 5) — shipped a clean SaaS landing page and a working particle galaxy one-shot
- Fast on Apple Silicon — 2.4s cold start, ~35 tokens/sec on an M4 Max
Trade-offs
- Half its one-shots shipped broken on the bench — a missing canvas append, a missing render loop, and an uncompiled WebGL shader
- Far below frontier models on complex 3D / WebGL / games — strongest on pages and simple canvas work, not simulations
Pricing & context — the spec sheet
| Spec | Fugu Ultra | Gemma-4 12B Coder |
|---|---|---|
| Vendor | Sakana AI | Community (Gemma-4 · local) |
| Context window | 272,000 tokens with the standard rate. Calls exceeding 272K context are billed at the higher 'long-context' rates. | 256,000 tokens |
| Price | $5 / 1M input · $30 / 1M output (Fugu Ultra) | Free · runs locally |
| Pricing detail | Sakana's multi-agent orchestration: a single API call internally dispatches to multiple frontier models and synthesises the answer. Subscription plans run $20-$200/mo (Standard / Pro / Max); PAYG is $5/M input + $30/M output for Fugu Ultra. Direct competitor to OpenRouter Fusion's panel approach. | A community fine-tune of Google's Gemma-4 12B (xentriom/gemma-4-12B-coder-fable5-composer2.5-v1), Apache-2.0. Free to download and run 100% offline on your own Mac via Ollama — no API, no per-token bill. The Q4_K_M build is 7.4GB. |
| Release | 2026-06-15 | 2026-06 |
| Bench coverage | 5/5 scored · avg 7.60/10 | 6/6 scored · avg 4.25/10 |
The verdict — which should you pick?
Across 2 scored shared tasks, Fugu Ultra averaged 8.75/10, beating Gemma-4 12B Coder's 6.00/10 by 2.75 points. Pick Fugu Ultra when the build has to ship on the first prompt and you can afford the trade-offs in the comparison below.
If you only run one of these inside your stack, the head-to-head average above is the call. If you can run both, my honest play is to wire Fugu Ultra and Gemma-4 12B Coder both into the Agent Operating System and dispatch each from the kanban by task type — teams that want fusion-class quality but need a different vendor risk profile → Fugu Ultra, free, private, offline coding where nothing can leave your machine → Gemma-4 12B Coder. That's the same setup I run for the 3,600+ founders inside the AI Profit Boardroom.
FAQ — Fugu Ultra vs Gemma-4 12B Coder
Which is better, Fugu Ultra or Gemma-4 12B Coder?
On Goldie Bench, Fugu Ultra averages 8.75/10 across the shared tasks, with 3 gold, 1 silver, 0 bronze overall. Gemma-4 12B Coder averages 6.00/10, with 0 gold, 0 silver, 0 bronze. Fugu Ultra wins the head-to-head 2–0.
How much does Fugu Ultra cost vs Gemma-4 12B Coder?
Fugu Ultra: Sakana's multi-agent orchestration: a single API call internally dispatches to multiple frontier models and synthesises the answer. Subscription plans run $20-$200/mo (Standard / Pro / Max); PAYG is $5/M input + $30/M output for Fugu Ultra. Direct competitor to OpenRouter Fusion's panel approach. Gemma-4 12B Coder: A community fine-tune of Google's Gemma-4 12B (xentriom/gemma-4-12B-coder-fable5-composer2.5-v1), Apache-2.0. Free to download and run 100% offline on your own Mac via Ollama — no API, no per-token bill. The Q4_K_M build is 7.4GB.
What's the context window for Fugu Ultra vs Gemma-4 12B Coder?
Fugu Ultra has a 272,000 tokens with the standard rate. Calls exceeding 272K context are billed at the higher 'long-context' rates. context window. Gemma-4 12B Coder has a 256,000 tokens context window.
When should I pick Fugu Ultra over Gemma-4 12B Coder?
Pick Fugu Ultra for: Teams that want Fusion-class quality but need a different vendor risk profile; Operators avoiding export-controlled providers (Sakana emphasises this in their pitch); Deep-research workflows where ensemble verdicts beat single-model answers. The trade-off is the weaknesses we logged on the bench: Panel orchestration adds latency — even a 'pong' burns ~2k orchestration tokens; Newer than Fusion; less community calibration on long-tail prompts.
When should I pick Gemma-4 12B Coder over Fugu Ultra?
Pick Gemma-4 12B Coder for: Free, private, offline coding where nothing can leave your machine; Landing pages, simple canvas builds, and code you'll review before shipping; Anyone who wants a $0 local coder wired into their Agent OS. The trade-off is the weaknesses we logged on the bench: Half its one-shots shipped broken on the bench — a missing canvas append, a missing render loop, and an uncompiled WebGL shader; Far below frontier models on complex 3D / WebGL / games — strongest on pages and simple canvas work, not simulations.
How does Goldie Bench score Fugu Ultra vs Gemma-4 12B Coder?
Every demo on this page was built by Julian Goldie inside the Agent Operating System — same fixed prompt for both models, one shot, single HTML file out. Each result gets a 0–10 score on whether it ran, how close it hit the brief, and how good it looked. The highest score on each task gets gold; second gets silver; third gets bronze. See methodology for full provenance.
Related comparisons
Other head-to-heads using the same scoring system:
Fugu Ultra vs Opus 4.8 Gemma-4 12B Coder vs Opus 4.8 Fugu Ultra vs GLM-5.2 Gemma-4 12B Coder vs GLM-5.2 Fugu Ultra vs Grok Gemma-4 12B Coder vs Grok Fugu Ultra vs Fusion Gemma-4 12B Coder vs FusionFull model pages: Fugu Ultra · Gemma-4 12B Coder · back to the leaderboard
Run this stack yourself.
Every demo on this bench was built inside the Agent Operating System — one prompt, one shot, single HTML file out. The Agent OS, the prompts, the templates, the weekly walkthroughs and 3,600+ founders shipping with it every day all live inside the AI Profit Boardroom.









